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A classical example of a word equation is the commutation equation =, in which is an unknown and is a constant word. It is well-known [ 4 ] that the solutions of the commutation equation are exactly those morphisms h {\displaystyle h} mapping x {\displaystyle x} to some power of w {\displaystyle w} .
A more efficient method would never repeat the same distance calculation. For example, the Levenshtein distance of all possible suffixes might be stored in an array , where [] [] is the distance between the last characters of string s and the last characters of string t. The table is easy to construct one row at a time starting with row 0.
The difference between the two algorithms consists in that the optimal string alignment algorithm computes the number of edit operations needed to make the strings equal under the condition that no substring is edited more than once, whereas the second one presents no such restriction. Take for example the edit distance between CA and ABC.
In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other.
One possible definition of the approximate string matching problem is the following: Given a pattern string =... and a text string = …, find a substring ′, = ′ … in T, which, of all substrings of T, has the smallest edit distance to the pattern P.
For a fixed length n, the Hamming distance is a metric on the set of the words of length n (also known as a Hamming space), as it fulfills the conditions of non-negativity, symmetry, the Hamming distance of two words is 0 if and only if the two words are identical, and it satisfies the triangle inequality as well: [2] Indeed, if we fix three words a, b and c, then whenever there is a ...
For example, the strings "Sam" and "Samuel" can be considered to be close. [1] A string metric provides a number indicating an algorithm-specific indication of distance. The most widely known string metric is a rudimentary one called the Levenshtein distance (also known as edit distance). [ 2 ]
For example, if x, y and z are elements of a group G, then xy, z −1 xzz and y −1 zxx −1 yz −1 are words in the set {x, y, z}. Two different words may evaluate to the same value in G , [ 1 ] or even in every group. [ 2 ]